gitllama 0.2.0

AI-powered git automation tool - clone, branch, change, commit, push with intelligence

GitLlama 🦙🤖

AI-powered git automation tool. Let AI intelligently clone, branch, change, commit, and push your code.

Features

• AI-Powered Decision Making: Uses Ollama LLMs to make intelligent decisions
• Smart Repository Analysis: AI explores and understands your project structure
• Intelligent Branch Naming: AI suggests meaningful branch names based on context
• Automated File Operations: AI decides what files to create, modify, or delete
• Context-Aware Commits: AI generates meaningful commit messages
• Fallback Mode: Works without AI for simple automation

Installation

pip install gitllama

Prerequisites

For AI features, you need Ollama running locally:

# Install Ollama (if not already installed)
curl -fsSL https://ollama.com/install.sh | sh

# Start Ollama server
ollama serve

# Pull a model (recommended for this tool)
ollama pull llama3.2:3b

Usage

Basic AI-powered usage:

gitllama https://github.com/user/repo.git

With custom model:

gitllama https://github.com/user/repo.git --model codellama:7b

Manual branch name (AI still handles other decisions):

gitllama https://github.com/user/repo.git --branch feature/my-improvement

Manual commit message:

gitllama https://github.com/user/repo.git --message "feat: add new feature"

Disable AI (simple automation):

gitllama https://github.com/user/repo.git --no-ai

What it does

1. Clones the repository
2. AI explores the project - reads files, understands structure
3. AI decides on branch name - meaningful and context-aware
4. AI makes intelligent changes - creates, modifies, or deletes files
5. AI generates commit message - follows conventional commit format
6. Pushes to remote

Python API

from gitllama import GitAutomator, AICoordinator

# With AI
ai = AICoordinator(model="llama3.2:3b")
with GitAutomator(ai_coordinator=ai) as automator:
    results = automator.run_full_workflow(
        git_url="https://github.com/user/repo.git"
    )
    print(f"Success: {results['success']}")
    print(f"AI Analysis: {results.get('ai_analysis')}")

# Without AI
with GitAutomator() as automator:
    results = automator.run_full_workflow(
        git_url="https://github.com/user/repo.git",
        branch_name="my-branch",
        commit_message="My changes"
    )

AI Models

The tool works with any Ollama model. Recommended models:

• llama3.2:3b - Fast and efficient (default)
• codellama:7b - Better for code-heavy repositories
• mistral:7b - Good general purpose
• gemma2:2b - Very fast, good for simple tasks

Configuration

# Use a different Ollama server
gitllama https://github.com/user/repo.git --ollama-url http://remote-server:11434

# Verbose output for debugging
gitllama https://github.com/user/repo.git --verbose

How AI Makes Decisions

1. Repository Exploration: AI reads key files to understand project type, technologies, and structure
2. Branch Naming: Based on project context, suggests descriptive branch names
3. File Operations: Decides whether to:
   • Create new files (documentation, configs, utilities)
   • Modify existing files (improvements, fixes)
   • Delete unnecessary files
4. Commit Messages: Generates conventional commit format messages based on changes

Development

git clone https://github.com/your-org/gitllama.git
cd gitllama
pip install -e ".[dev]"

License

GPL v3 - see LICENSE file.